Hsien-Wen Cheng and Lan-Rong Dung
Department of Electrical and Control Engineering
National Chiao Tung University
Hsinchu, 300 Taiwan
E-mail: lennon@cn.nctu.edu.tw

This paper presents a novel power-aware motion estimation architecture for battery-
powered multimedia devices. As the battery status changes, the proposed architecture
adaptively performs graceful tradeoffs between power consumption and compression
quality. The tradeoffs are considered to be graceful in that the proposed architecture
is scalable with changing conditions and the compression quality is slightly degraded as
the available energy is depleted. The key to such tradeoffs lies in a content-based subsample
algorithm, first proposed in this paper. As the available energy decreases, the algorithm
raises the subsample rate for maximizing the battery lifetime. Differently from
the existing subsample algorithms, the content-based algorithm first extracts edge pixels
from a macro-block and then subsamples the remaining low-frequency part. By doing so,
we can alleviate the aliasing problem and, thus, limit the quality degradation as the subsample
rate increases. Given a power consumption mode, the proposed architecture first
performs edge extraction to generate a turn-off mask and then uses the turn-off mask to
reduce the switch activities of processing elements (PEs) in a semi-systolic array. The
reduction of switch activities results in significant power consumption savings. To
achieve a high degree of scalability and qualified power-awareness, we use an adaptive
control mechanism to set the threshold value for edge determination and make the reduction
of switch activities rather stationary. As shown by experimental results, the architecture
can dynamically operate in different power consumption modes with little quality
degradation according to the remaining capacity of the battery pack while the power
overhead of edge extraction is kept under 0.8%

Received February 9, 2004; revised July 6, 2004; accepted July 27, 2004.
Communicated by Pau-Choo Chung.
* This work was supported in part by the National Science Council of Taiwan, R.O.C., under grant No. NSC
92-2220-E-009-033.